TensorScatterUpdate

public final class TensorScatterUpdate

Scatter `updates` into an existing tensor according to `indices`.

This operation creates a new tensor by applying sparse `updates` to the passed in `tensor`. This operation is very similar to `tf.scatter_nd`, except that the updates are scattered onto an existing tensor (as opposed to a zero-tensor). If the memory for the existing tensor cannot be re-used, a copy is made and updated.

If `indices` contains duplicates, then we pick the last update for the index.

If an out of bound index is found on CPU, an error is returned.

WARNING: There are some GPU specific semantics for this operation. - If an out of bound index is found, the index is ignored. - The order in which updates are applied is nondeterministic, so the output will be nondeterministic if `indices` contains duplicates.

`indices` is an integer tensor containing indices into a new tensor of shape `shape`.

  • `indices` must have at least 2 axes: `(num_updates, index_depth)`.
  • The last axis of `indices` is how deep to index into `tensor` so this index depth must be less than the rank of `tensor`: `indices.shape[-1] <= tensor.ndim`
if `indices.shape[-1] = tensor.rank` this Op indexes and updates scalar elements. if `indices.shape[-1] < tensor.rank` it indexes and updates slices of the input `tensor`.

Each `update` has a rank of `tensor.rank - indices.shape[-1]`. The overall shape of `updates` is:

indices.shape[:-1] + tensor.shape[indices.shape[-1]:]
 
For usage examples see the python [tf.tensor_scatter_nd_update]( https://www.tensorflow.org/api_docs/python/tf/tensor_scatter_nd_update) function

Public Methods

Output<T>
asOutput()
Returns the symbolic handle of a tensor.
static <T, U extends Number> TensorScatterUpdate<T>
create(Scope scope, Operand<T> tensor, Operand<U> indices, Operand<T> updates)
Factory method to create a class wrapping a new TensorScatterUpdate operation.
Output<T>
output()
A new tensor with the given shape and updates applied according to the indices.

Inherited Methods

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static TensorScatterUpdate<T> create (Scope scope, Operand<T> tensor, Operand<U> indices, Operand<T> updates)

Factory method to create a class wrapping a new TensorScatterUpdate operation.

Parameters
scope current scope
tensor Tensor to copy/update.
indices Index tensor.
updates Updates to scatter into output.
Returns
  • a new instance of TensorScatterUpdate

public Output<T> output ()

A new tensor with the given shape and updates applied according to the indices.